The present invention relates to image processing and, more particularly, but not exclusively to extracting objects of interest from video images captured during a sport event.
In recent years, the use of image processing and computer vision has been gaining more and more popularity in a variety of fields and industries. Some known industrial applications of image processing and computer vision include, for example, security surveillance systems, operational management systems (say in a retail industry environment), tactical battlefield systems, etc.
The extraction of objects of interest from video images is an aspect of video analysis.
One of the techniques widely used in the fields of image processing and computer vision is background subtraction.
Background subtraction is a technique in which an image's foreground is extracted for further processing, usually for recognition of objects of interest.
Generally, an image's foreground is made of regions of the image, which are occupied by objects of interest (humans, cars, text, etc.). After a stage of image preprocessing (which may include image noise removal, morphology based analysis, etc.), object localization may be required, which object localization may make use of background subtraction.
Background subtraction is widely used for detecting moving objects (say cars or pedestrians) in videos, from static cameras, the rationale being one of detecting the moving objects from the difference between the current frame and a reference background template, also referred to as “background image” or “background model”, which is made of static objects such as a building or a traffic light positioned at a road intersection.
Objection extraction by background subtraction is often done if the image in question is a part of a video stream. Background subtraction provides important cues for numerous applications in computer vision, for example surveillance tracking or human poses estimation.